13 set - Roma
Mercor
ppbFluent Language Skills Required: /b Korean. Native fluency in Korean, including full command of Hangul, is required for this position. All annotation and transcription work is performed in Korean. /ph3Why This Role Exists /h3pDocument understanding breaks down fastest in the languages that parsing and vision-language models rarely see. This project builds training data for exactly those languages: Korean, alongside Japanese and five Indic scripts. Each task takes a real, publicly available PDF page and produces a complete structural map of that page, paired with a faithful transcription of every text region in the original script. /ppThe dataset deliberately concentrates on the material models handle worst: handwriting, dense multi-column layouts, tables, diagrams, and mixed-script pages. Documents are drawn from newspapers, textbooks, examinations, and everyday formats such as flyers, forms, manuals, menus, brochures, notices and worksheets, so that the corpus reflects the real diversity of Korean documents rather than a narrow band of easily parsed ones. /ppDelivered work is human-authored throughout. Component identification, component typing, reading order and all transcription are performed by people, not generated by parsing models. /ph3What You'll Do /h3ullipOpen and check a task: pages are provided, so you do not source documents yourself. We find the PDFs and upload them for you. Before annotating, confirm the page is in Korean, is legible, has real content, and shows no personal details /p /lilipAnnotate structure:
identify and bound every meaningful region of the page - document title, section heading, paragraph, list, table, figure, diagram, caption, formula, question, answer field - and assign each a component type and a reading-order index /p /lilipRecord relationships: link each region to the figure or table it belongs to through a parent component identifier /p /lilipTranscribe faithfully: reproduce all text exactly as it appears in Hangul, including any hanja and handwritten content, flagging any region where the source is not legible /p /lilipCapture page metadata: language, document type, source, page dimensions, and flags for tables, formulas and handwriting /p /lilipReview a colleague's work: every task is reviewed end to end by a second Korean expert, and experienced annotators take on that review /p /li /ulh3Who You Are /h3ullipYou are a native Korean speaker with full command of Hangul, including hanja where it appears in older or formal documents /p /lilipYou have worked in bilingual transcription, translation, editorial work, or AI training data, ideally with reviewer experience /p /lilipYou are exact: character-level accuracy matters more here than speed, and a single wrong jamo is a defect /p /lilipYou are systematic:
you apply a taxonomy consistently across hundreds of pages rather than improvising per document /p /lilipYou are comfortable with unfamiliar layouts: multi-column newspapers, exam papers, handwritten forms /p /li /ulh3Nice-to-Have Specialties /h3ullipAI training data: annotation, labeling, grading, or bilingual evaluation for training datasets /p /lilipTranscription and localization: MTPE, subtitling, bilingual QA, OCR correction or post-editing /p /lilipDocument production: typesetting, copy-editing, proofreading, or digitization of Korean-language material /p /lilipScript and encoding: Unicode normalization, Korean input methods, Hangul jamo composition, and hanja handling /p /li /ulh3What Success Looks Like /h3ullipEvery meaningful region on the page is captured, correctly bounded and correctly typed /p /lilipReading order reflects how the page is actually read, including across columns /p /lilipTranscriptions match the source character for character, in Hangul rather than romanization /p /lilipYour tasks pass second-expert review the first time /p /lilipUnsuitable pages are flagged up front rather than after thirty minutes of work /p /li /ulh3Why Join Mercor /h3ullipBuild the training data that makes document AI work in scripts it currently handles badly /p /lilipWork from real published Korean documents rather than synthetic or templated pages /p /lilipQuality leads on this project: accuracy is the first measure, with handling time tracked alongside it /p /li /ul /p #J-18808-Ljbffr
13 set - Italia
UNIVERSO
13 set - Catanzaro
Sentra Energia
13 set - Milano
Mantea Care
13 set - Campobasso
Cpm Italy